Summary of Work

GOES-R and JPSS Proving GroundsBridging the gap from research to operations
Role: Co-Investigator

The Geostationary Operational Environmental Satellite R-Series (GOES-R) and Joint Polar Satellite System (JPSS)
Proving Grounds are an orchestrated effort among several cooperative institutes, including CIMSS, and the
National Oceanic and Atmospheric Administration (NOAA) to prepare the primary users of geostationary and polar satellite data,
forecasters at the National Weather Service (NWS), for the launch and operational activation of GOES-R and JPSS. Compared
to the current GOES series, the amount of raw GOES-R data processed will increase by 60, with additional products derived from
the increase in spatial, temporal, and spectral resolutions. This continuing multi-year effort includes conducting training
at NWS units and constructing virtual learning activities, finding new ways to use existing space-based resources for emulating
GOES-R and JPSS imagery and science products, such as exploiting the capabilities of the Suomi National Polar-orbiting
Partnership (NPP), readying GOES-R and JPSS Proving Ground products for operations through incorporation into the Advanced
Weather Interactive Processing System (AWIPS), and building a close relationship between algorithm developers and users to
ensure a two-way dialogue that results in the best possible transition from current GOES to GOES-R deployment, and from NPP to
JPSS.

The National Aeronautics and Space Administration (NASA) operate a series of polar-orbiting satellites
which are used to make atmospheric measurements. These space-based observations have been shown useful in improving
numerical weather prediction simulations. This work includes using the Weather Research and Forecast (WRF) Model with
initial conditions modified by data from two NASA satellites equipped with a MODerate Resolution Imaging Spectroradiometer
(MODIS) to assess the impact of space-based data on mesoscale weather simulations (occurring on a horizontal grid of 20-kilometer
spacing or less) over regional sectors. A particularly notable region is the Great Lakes, where the marine-modified
atmosphere plays a significant role in the weather of coastal communities. The end goal is to show improved temperature
and moisture forecasts and provide this data to the NWS in real-time.

NWS meteorologists are required to produce gridded sky cover forecasts as part of their routine duties and
submit them to the National Digital Forecast Database (NDFD). Discrepancies in the NDFD sky cover forecast remain despite
progress with other weather elements since the inception of the NDFD. There are two causes for this. First, a
suitable sky cover analysis does not exist for validation purposes. Second, the diagnostic sky cover formulation currently
used in numerical weather prediction models, which provide input to the NDFD, does not adequately represent some cloud patterns. This
research devises a methodology to incorporate both geostationary satellite and in-situ observations of cloud into a
single sky cover analysis. Using an optimization methodology, this analysis is then compared to numerical weather model
fields to establish a linear correlation between sky cover and prognostic model variables. The objective is to improve
short-term sky cover forecasts.